Global consistency mapping with a hybrid representation

This paper presents a methodology of error correction applied to autonomously mapping large scale cyclic environment by mobile robots based on laser scan measurements. The model of the unknown indoor environment is structured as a hybrid representation, both topological and geometrical, which is inc...

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Bibliographic Details
Main Authors: Victorino, A.C., Rives, P.
Format: Conference Proceeding
Language:English
Subjects:
cyclic environment
elastic error correction
Error correction
hybrid model
Indoor environments
Large-scale systems
Laser modes
mapping
Minimization methods
mobile robot
Navigation
Orbital robotics
Robot sensing systems
Robustness
Solid modeling
Online Access:Request full text
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Summary:This paper presents a methodology of error correction applied to autonomously mapping large scale cyclic environment by mobile robots based on laser scan measurements. The model of the unknown indoor environment is structured as a hybrid representation, both topological and geometrical, which is incrementally built during the exploration task. The correction methodology is based on the minimization of geometric elastic relations between different places of the environment, constrained by rigid geometrical model inside each place. Results are presented which shows the minimization of inconsistencies related to an autonomous constructed hybrid model by the application of the proposed methodology.
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2005.1545337